The objective is to investigate the heterogeneity of schizophrenia-a chronic mental disorder. It is proposed that there are three bio- behavioral dimensions in this disorder-positive, negative and cognitive. The varying severity of each dimension and degree of their coexistence within a patient accounts for the clinical and biological heterogeneity of the disorder. Specific hypotheses regarding the components of these dimensions and their relationships will be investigated. The positive dimension refers to dopaminergic overactivity and is assessed by (a) severity of positive psychotic symptoms (b) behavioral response to amphetamine challenge (ACT) and, (c) treatment response to neuroleptic medication. The negative dimension is that of structural brain changes and will be assessed by magnetic resonance imaging of the brain to determine ventricle size, cortical atrophy, frontal lobe size and, proton relaxation time (T2) of the frontal, temporal and limbic cortex. Premorbid sociality, social deterioration and negative symptoms form the behavioral part of this dimension. The cognitive dimension consists of impaired attention and information processing ability. It is assessed by rating (a) persistent formal thought disorder (b) errors in continuous task performance and (c) dysfunction in smooth pursuit eye movement. Sixty subjects with a research diagnosis of schizophrenia will be studied over a four year period. Positive, negative and cognitive symptoms will be measured during different phases of the illness using separate rating scales to enhance their comprehensive and accurate assessment. State of the art equipment such as a 1.5 tesla magnetic resonance image and infra- red technology for eye movements will be used to obtain the biological measures. Assessment of negative symptom and the ACT will be done in a drug-free state. Confirmatory factor analysis and multiple correlation analyses will be used to test the construct validity of the three dimensions. Canonical correlation will be used to assess the interdimensional relationships. Linear regression will be used to assess the predictive power of the biological measures. For instance how much treatment response can be predicted by the amphetamine test and how much deterioration can be predicted by the structural brain changes.